DocumentCode :
265174
Title :
Paid Search: Modeling Rank Dependent Behavior
Author :
Anderson, Chris K. ; Ming Cheng
Author_Institution :
Sch. of Hotel Adm., Cornell Univ., Ithaca, NY, USA
fYear :
2014
fDate :
6-9 Jan. 2014
Firstpage :
3093
Lastpage :
3099
Abstract :
Using disaggregated data from a Chinese search engine we jointly model ad rank and performance for hospitality related keyword searches. As a result of our modeling framework we can better determine the optimal keyword bidding strategy for an advertiser given the search engine´s control over ad rank. Our approach removes rank bias in estimating keyword bidding performance. We then illustrate the impact of branded versus generic keyword searches, outlining profit maximizing keyword bidding.
Keywords :
advertising; query processing; search engines; tendering; Chinese search engine; ad rank modelling; branded keyword search; disaggregated data; generic keyword search; hospitality-related keyword search; keyword bidding performance estimation; optimal keyword bidding strategy; paid search process; performance modelling; rank bias removal; rank dependent behavior modeling; Advertising; Companies; Data models; Internet; Joints; Mathematical model; Search engines; Logistic Regression; Search Engine Marketing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences (HICSS), 2014 47th Hawaii International Conference on
Conference_Location :
Waikoloa, HI
Type :
conf
DOI :
10.1109/HICSS.2014.385
Filename :
6758986
Link To Document :
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